1. Field of the Invention
This present invention relates to an image processing method, and more particularly to a method for producing an enhanced-resolution image by use of a plurality of low-resolution images. With respect to the technology background of the method of the invention, please refer to the following references:
[1] M. Irani and S. Peleg, “Improving Resolution by Image Registration,” CVGIP:Graphical Models and Image Proc.,1991, Vol. 53, pp. 231-239;
[2] R. Y. Tsai and T. S. Huang, “Multiframe Image Restoration and Registration,” in Advances in Computer Vision and Image Processing, Vol. 1 (T. S. Huang, ed.), Greenwich, CT: Jai Press, 1984, pp. 317-339;
[3] P. Cheeseman, B. Kanefsky, R. Kruft, J. Stutz, and R. Hanson, “Super-Resolved Surface Reconstruction from Multiple Images,” NASA Technical Report FIA-94-12, 1994;
[4] A. M. Tekalp, M. K. Ozkan, and M. I. Sezan, “High-Resolution Image Reconstruction for Lower-Resolution Image Sequences and Space-Varying Image Restoration,” IEEE International Conference on Acoustics, Speech, and Signal Processing, San Francisco, Calif., 1992, Vol. III, pp. 169-172;
[5] R. C. Gonzalez and R. E. Woods, Digital Image Processing, Addison-Wesley, Reading, Mass., 1992;
[6] W. K. Pratt, Digital Image Processing, 2nd Ed., Wiley, New York, 2001;
[7] U.S. Pat. No. 6,330,344; and
[8] U.S. Pat. No. 5,969,848.
2. Description of the Prior Art
Due to environmental constraints and resolution of image sensors, sometimes we can only get low-resolution images. In order to improve the image quality and resolution seen by human eyes, more than one input image is required. With image sequences, a blurring scene, a dim figure, or an unclear object of poor quality can be reconstructed to an enhanced-resolution output image and can then be easily observed and recognized.
Prior researches regarding the reconstruction of an enhanced-resolution image by use of low-resolution images are mainly divided into iterative methods [1], frequency domain methods [2], and Bayesian statistical methods [3]. In aforesaid methods, so far, the iterative algorithm that has been developed by Irani [1] in 1991 and reconstructs an enhanced-resolution image mainly by image registration, is still most reliable in the prior arts regarding the reconstruction of an enhanced-resolution image. The iterative method mainly consists of three phases: initial guess, imaging process, and reconstruction process. The procedures of the three phases of the iterative method will be described in details in the detailed description of the invention.
However, it is noticed that the iterative method will consume more computation time as the magnification factor predetermined in the iterative method becomes larger, i.e., the size of the reconstructed image becomes larger. Typically, the runtime of image reconstruction by the iterative method is on the order of hours and depends on the performance of computer system.
Therefore, an objective of the invention is to provide a method for reconstructing an enhanced-resolution image with improved enhanced-resolution algorithms, which is based on Irani's iterative method and employs well-suggested initial interpolation, automatic image selection and robust image registration. Further, the enhanced-resolution image reconstructed by the method of the invention can be performed by an image enhancement post-process to enhance image quality thereof.
Whereas the conventional systems of the reconstruction of enhanced-resolution images work well only as the low-resolution image sequences are captured by moving a stationary camera in a constant displacement in relation to the whole scene, i.e., the targets, needed to be reconstructed, associate with stationary scenes. Therefore, another objective of the invention is to provide a method for reconstructing an enhanced-resolution image, which work well not only for the conditions as the targets, needed to be reconstructed, associate with stationary scenes, but also for the conditions as the targets, needed to be reconstructed, associate with moving objects.